A Systolic Algorithm for Euclidean Distance Transform

Authors:
Masafumi Miyazawa;Peifeng Zeng;Naoyuki Iso;Tomio Hirata
Affiliations:
-;IEEE;-;IEEE
Venue:
IEEE Transactions on Pattern Analysis and Machine Intelligence
Year:
2006

Citing 8
Cited 0

An efficient algorithm for complete Euclidean distance transform on mesh-connected SIMD

Parallel Computing
An optimal parallel algorithm for the Euclidean distance maps of 2-D binary images

Information Processing Letters
Designing systolic architectures for complete Euclidean distance transform

Journal of VLSI Signal Processing Systems
A unified linear-time algorithm for computing distance maps

Information Processing Letters
Parallel computation of the Euclidean distance transform on the mesh of trees and the hypercube computer

Computer Vision and Image Understanding
Sequential Operations in Digital Picture Processing

Journal of the ACM (JACM)
Linear Time Euclidean Distance Algorithms

IEEE Transactions on Pattern Analysis and Machine Intelligence
A Linear Time Algorithm for Computing Exact Euclidean Distance Transforms of Binary Images in Arbitrary Dimensions

IEEE Transactions on Pattern Analysis and Machine Intelligence

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Abstract

The Euclidean distance transform is one of the fundamental operations in image processing. It has been widely used in computer vision, pattern recognition, morphological filtering, and robotics. This paper proposes a systolic algorithm that computes the Euclidean distance map of an N\times N binary image in 3N clocks on 2N^2 processing cells. The algorithm is designed so that the hardware resources are reduced; especially no mulitipliers are used and, thus, it facilitates VLSI implementation.